Text Classification Using a Bidirectional Recurrent Neural Network with an Attention Mechanism

Text classification is an important semantic processing task in the field of natural language processing (NLP). Traditional text-classifying systems often rely on human-designed features, and most of existing methods fail to obtain the sentence information completely. In this paper, we design a recurrent structure to represent the input sentence, and apply attention mechanism to capture the most important semantic information in a sentence. We conduct experiments on the Internet Movie Database (IMDB). The experimental result shows that our method outperforms most of methods of text classification.